Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities

IF 34.4 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Communications Surveys and Tutorials Pub Date : 2023-03-13 DOI:10.1109/COMST.2023.3256323

Stephanie Baker;Wei Xiang

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引用次数: 14

Abstract

Healthcare systems are under increasing strain due to a myriad of factors, from a steadily ageing global population to the current COVID-19 pandemic. In a world where we have needed to be connected but apart, the need for enhanced remote and at-home healthcare has become clear. The Internet of Things (IoT) offers a promising solution. The IoT has created a highly connected world, with billions of devices collecting and communicating data from a range of applications, including healthcare. Due to these high volumes of data, a natural synergy with Artificial Intelligence (AI) has become apparent - big data both enables and requires AI to interpret, understand, and make decisions that provide optimal outcomes. In this extensive survey, we thoroughly explore this synergy through an examination of the field of the Artificial Intelligence of Things (AIoT) for healthcare. This work begins by briefly establishing a unified architecture of AIoT in a healthcare context, including sensors and devices, novel communication technologies, and cross-layer AI. We then examine recent research pertaining to each component of the AIoT architecture from several key perspectives, identifying promising technologies, challenges, and opportunities that are unique to healthcare. Several examples of real-world AIoT healthcare use cases are then presented to illustrate the potential of these technologies. Lastly, this work outlines promising directions for future research in AIoT for healthcare.

查看原文本刊更多论文

面向更智能医疗的物联网人工智能:进展、挑战和机遇调查

从全球人口稳步老龄化到当前的新冠肺炎大流行，由于多种因素，医疗保健系统正面临越来越大的压力。在一个我们需要联系但又需要分开的世界里，对增强远程和家庭医疗保健的需求已经变得显而易见。物联网（IoT）提供了一个很有前景的解决方案。物联网创造了一个高度互联的世界，数十亿台设备从包括医疗保健在内的一系列应用程序中收集和通信数据。由于这些大量的数据，与人工智能（AI）的自然协同作用已经变得明显——大数据使人工智能能够并需要人工智能来解释、理解和做出提供最佳结果的决策。在这项广泛的调查中，我们通过对医疗保健人工智能（AIoT）领域的研究，深入探讨了这种协同作用。这项工作首先简要建立了医疗保健背景下AIoT的统一架构，包括传感器和设备、新型通信技术和跨层人工智能。然后，我们从几个关键角度审视了与AIoT架构的每个组件相关的最新研究，确定了医疗保健特有的有前景的技术、挑战和机遇。然后介绍了几个真实世界AIoT医疗保健用例的例子，以说明这些技术的潜力。最后，这项工作概述了未来医疗保健AIoT研究的有希望的方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Surveys and Tutorials COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

80.20

自引率

2.50%

发文量

审稿时长

6 months

期刊介绍： IEEE Communications Surveys & Tutorials is an online journal published by the IEEE Communications Society for tutorials and surveys covering all aspects of the communications field. Telecommunications technology is progressing at a rapid pace, and the IEEE Communications Society is committed to providing researchers and other professionals the information and tools to stay abreast. IEEE Communications Surveys and Tutorials focuses on integrating and adding understanding to the existing literature on communications, putting results in context. Whether searching for in-depth information about a familiar area or an introduction into a new area, IEEE Communications Surveys & Tutorials aims to be the premier source of peer-reviewed, comprehensive tutorials and surveys, and pointers to further sources. IEEE Communications Surveys & Tutorials publishes only articles exclusively written for IEEE Communications Surveys & Tutorials and go through a rigorous review process before their publication in the quarterly issues. A tutorial article in the IEEE Communications Surveys & Tutorials should be designed to help the reader to become familiar with and learn something specific about a chosen topic. In contrast, the term survey, as applied here, is defined to mean a survey of the literature. A survey article in IEEE Communications Surveys & Tutorials should provide a comprehensive review of developments in a selected area, covering its development from its inception to its current state and beyond, and illustrating its development through liberal citations from the literature. Both tutorials and surveys should be tutorial in nature and should be written in a style comprehensible to readers outside the specialty of the article.